Abstract

Internet memes are increasingly used to sway and possibly manipulate public opinion, thus prompting the need to study their propagation, evolution, and influence across the Web. In this paper, we detect and measure the propagation of memes across multiple Web communities, using a processing pipeline based on perceptual hashing and clustering techniques, and a dataset of 160M images from 2.6B posts gathered from Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab over the course of 13 months. We group the images posted on fringe Web communities (/pol/, Gab, and The_Donald subreddit) into clusters, annotate them using meme metadata obtained from Know Your Meme, and also map images from mainstream communities (Twitter and Reddit) to the clusters.

Our analysis provides an assessment of the popularity and diversity of memes in the context of each community, showing, e.g., that racist memes are extremely common in fringe Web communities. We also find a substantial number of politics-related memes on both mainstream and fringe Web communities, supporting media reports that memes might be used to enhance or harm politicians. Finally, we use Hawkes processes to model the interplay between Web communities and quantify their reciprocal influence, finding that /pol/ substantially influences the meme ecosystem with the number of memes it produces, while The_Donald has a higher success rate in pushing them to other communities. […]

Meme Analysis

In summary, the main take-aways of our analysis include:

1. Fringe Web communities use many variants of memes related to politics and world events, possibly aiming to share weaponized information about them. For instance, Donald Trump is the KYM entry with the largest number of clusters in /pol/ (2.2%), The Donald (6.1%), and Gab (2.2%).

2. /pol/ and Gab share hateful and racist memes at a higher rate than mainstream communities, as we find a considerable number of anti-semitic and pro-Nazi clusters (e.g., The Happy Merchant meme appears in 1.3% of all /pol/ annotated clusters and 2.2% of Gab’s, while Adolf Hitler in 0.6% of /pol/’s). This trend is steady over time for /pol/ but ramping up for Gab.

3. Seemingly “neutral” memes, like Pepe the Frog (or one of its variants), are used in conjunction with other memes to incite hate or influence public opinion on world events, e.g., with images related to terrorist organizations like ISIS or world events such as Brexit.

4. Our custom distance metric successfully allows us to study the interplay and the overlap of memes, as showcased by the visualizations of the clusters and the dendrogram (see Figure 6 and 7).

5. Reddit users are more interested in politics-related memes than other type of memes. That said, when looking at individual subreddits, we find that The Donald is the most active one when it comes to posting memes in general. It is also the subreddit where most racism and politicsrelated memes are posted. […]

Influence Estimation

There are several take-aways from our measurement of influence. We show that /pol/ is, generally speaking, the most influential disseminator of memes in terms of raw influence, In particular, it is more influential in spreading racist memes than non-racist one, and this difference is deeper than in any other community. There is one notable exception: /pol/ is more influential in terms of non-racist memes on The Donald. Relatedly, /pol/ has generally more influence in terms of spreading political memes than other communities. When looking at the normalized influence, however, we surface a more interesting result: /pol/ is the least efficient in terms of influence while The Donald is the most efficient.

This provides new insight into the meme ecosystem: there are clearly evolutionary effects. Many meme postings do not result in further dissemination, and one of the key components to ensuring they are disseminated is ensuring that new “offspring” are continuously produced. /pol/’s “famed” meme magic, i.e., producing and heavily pushing memes, is thus the most likely explanation for /pol/’s influence on the Web in general.